Qwen3.8 Flash-Next

Headlines · 3

1. 2h
   XeMaya brings native Intel Arc inference to recent MoE models

   A developer built XeMaya, a fork of XeStrata that runs models natively on Intel Arc GPUs through SYCL and Level Zero. The early-alpha project reportedly supports DeepSeek V4.1 Flash and Coder, GLM 5.3 Flash, and Qwen3.8 Flash-Next, with preliminary prefill and generation results reported on an Ubuntu server. The developer cautioned that different model files, prompts, and GPU configurations made the comparisons uncontrolled, leaving further fixes and optimization needed.

   r/LocalLLaMA · 🔥 5
2. 2d
   4x Radeon R9700 runs Qwen3.8 Flash-Next at ~190 tok/s, 6,800 tok/s prefill

   A Reddit user (/u/Anarchaotic) posted initial benchmarks for a four-GPU Radeon R9700 system (3x Gigabyte, 1x XFX, all power-limited to 210W) running Radiance v1.17.0 with a qwen3.8-next-flash-fp8-iq4r-moe.rad MoE model on Ubuntu 26.04.1 and ROCm 10.1. Client-side measurements show one user writing at about 190 tok/s, aggregate prefill of about 6,800 tok/s regardless of user count, and agent follow-up turns returning the first token in 0.2-2.5 s at 80-225 tok/s per user with 94-99% prefix-cache hits. The reported worst case of eight simultaneous fresh 128K prompts took about 151 seconds for the first token, while the two middle cards reached 91 C hotspot and 92 C memory during prefill.

   r/LocalLLaMA · 🔥 0
3. 5d
   Qwen3.8 Flash-Next guide posts high local inference speeds amid quantization dispute

   A community guide reports that Basalt, Unsloth's UD-IQ3_XXS quantization, and the Lamina drafter delivered 195.6 tokens/s average decode and about 5,700 tokens/s prompt reads for Qwen3.8 Flash-Next in an OpenCode session on an RTX 5080. The author says Basalt reached roughly five times llama.cpp's drafted decode speed and seven times its prompt-read speed, while Unsloth's quantization achieved 3.247 WikiText perplexity versus BF16's 3.273. A separate Reddit post says Unsloth disputed the reproducibility of ISTA-DASLab's GSQ-RCO benchmark numbers and found similarly sized Unsloth quantizations performing better in its testing.

   r/LocalLLaMA · 🔥 0

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